The hardware and bandwidth for this mirror is donated by dogado GmbH, the Webhosting and Full Service-Cloud Provider. Check out our Wordpress Tutorial.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]dogado.de.
Have you ever dreamed of profiling, load testing your Shiny app at each commit, without having to manually run any script?
In this vignette, we’ll see how one can design and automate Shiny
apps audit pipelines with {shinytest2}
.
This case study consists of analyzing a particularly non-optimized
app, whose code is defined below. This app simulates a stiff oscillator,
also known as Van der Pol model.
Under the hood, this system (composed of 2 differential equations) is
integrated with the {deSolve}
package. Stiff systems need a
much smaller time step than classic systems, thereby requiring more time
to solve:
van_der_pol <- function(t, y, mu) {
d_x <- y[2]
d_y <- mu * (1 - y[1]^2) * y[2] - y[1]
list(c(X = d_x, Y = d_y))
}
server <- function(input, output) {
output$brussels <- renderPlot({
y0 <- c(X = input$X, Y = input$Y)
times <- seq(0, 1000, .01)
out <- ode(y0, times, van_der_pol, input$mu)
par(mfrow = c(1, 1))
plot(out[, 2:3], type = "l", xlab = "X", ylab = "Y", main = "state diagram")
})
}
ui <- fluidPage(
headerPanel("Van der Pol oscillator"),
sidebarLayout(
sidebarPanel(
h3("Init values"),
numericInput("X", label = "X", min = 0.0, max = 5, value = 1, step = 0.2),
numericInput("Y", label = "Y", min = 0.0, max = 5, value = 1, step = 0.2),
h3("Parameters"),
numericInput("mu", label = "mu", min = 0.0, max = 5, value = 1, step = 0.1)
),
mainPanel(
h3("Simulation results"),
plotOutput("brussels")
)
)
)
shinyApp(ui = ui, server = server)
As a first test, you can run the app by calling
runApp(system.file("vig-apps/non-optimized-app/", package = "shinytest2"))
locally and notice how slow it is to perform one computation. The next
question is, how does this app scale? The answer is likely “No it
doesn’t!”, but we would like to know exactly how bad it is. This is
where load testing comes to play.
Shiny app load testing aims at running multiple identical user sessions in parallel and measure the resulting app response. It answers many questions, such as:
A load test is composed a three phases:
{shinytest2}
, {shinyloadtest}
records a user session with
shinyloadtest::record_session()
.shinycannon
, able to simulate multiple sessions during a
chosen amount of time.shinyloadtest::load_runs()
and
an HTML report generated with
shinyloadtest::shinyloadtest_report()
.In general, the first step is done manually, that is, you play with
the app as if you were a real business user and stop the session when
satisfied. However, because of {shinytest2}
headless
capabilities, we could manipulate the app with {shinytest2}
helpers such as set_inputs
or raw JavaScript code to
achieve the same goal.
There is, however, a tiny technical obstacle to overcome. By default,
{shinytest2}
starts the app on a given port and the
headless browser, namely Chrome, is then connected to the same port.
This would be an issue with {shinyloadtest}
since the
recorder does not listen to the same port, which is 8600
.
In practice, we’ll have to:
8600
.8600
.You may have already noticed that when launching a Shiny app, you can’t run anything else in the R console while the app is live. The explanation is pretty simple: R performs tasks sequentially and can only perform one calculation at a time.
How do we start the app without blocking the main R process? We
leverage the {callr}
package, which exposes a convenient
API to start R processes in the background, that is, without blocking
the main R process. The code below shows how to start a Shiny app
located at path
on a specific port and run the load test
recorder on the same port:
# Main shiny app
shiny_bg <- function(path, port) {
options(shiny.port = port)
shiny::runApp(path)
}
# Start recorder
recorder_bg <- function(port) {
shinyloadtest::record_session(
target_app_url = sprintf("http://127.0.0.1:%s", port),
host = "127.0.0.1",
port = 8600,
output_file = "recording.log",
open_browser = FALSE
)
}
We can pass this to the start_r_bg()
function:
start_r_bg <- function(fun, path = NULL, port = 3515) {
# remove NULL elements
args <- Filter(Negate(is.null), list(path = path, port = port))
process <- callr::r_bg(
func = fun,
args = args,
stderr= "",
stdout = ""
)
while (any(is.na(pingr::ping_port("127.0.0.1", 3515)))) {
message("Waiting for Shiny app to start...")
Sys.sleep(0.1)
}
attempt::stop_if_not(
process$is_alive(),
msg = "Unable to launch the subprocess"
)
process
}
where r_bg()
starts a background R process, passing the
corresponding function and parameters. Besides, we provide some log
elements and safety guard in case the app can’t start. To launch the app
and recorder we can call:
The previous part was the most technical step. Now, we only have to
start a Chrome headless browser on port 8600
, where the
load test recorder runs. You’ll notice that {shinytest2}
also supports remote urls. We should increase the value of
load_timout
to 15 seconds to help us avoid producing this
annoying {shinytest2}
warning:
{shinytest2} R info 15:25:37.36 Error while initializing AppDriver:
Shiny app did not become stable in 10000ms.
# Start AppDriver with recorder url
chrome <- shinytest2::AppDriver$new("http://127.0.0.1:8600", load_timeout = 15 * 1000)
If your running under Linux OS, below shows the list of R processes running so far in the background:
$ netstat -lntp
Proto Recv-Q Send-Q Local Address Foreign Address State PID/Program name
tcp 0 0 127.0.0.1:8600 0.0.0.0:* LISTEN 361115/R
tcp 0 0 127.0.0.1:3515 0.0.0.0:* LISTEN 361101/R
tcp 0 0 127.0.0.1:44179 0.0.0.0:* LISTEN 359555/google-chrom
If everything is successful, you should see a Client
connected message in the R console. We then change the
mu
parameter input without forgetting the timeout:
We can inspect the logs with the help of
chrome$get_log()
, to check whether everything run
smoothly:
app$get_logs()
#> {shinytest2} R info 14:27:00.80 Start AppDriver initialization
#> {shinytest2} R info 14:27:00.82 Creating new ChromoteSession
#> {shinytest2} R info 14:27:02.20 Navigating to Shiny app
#> {shinytest2} R info 14:27:02.57 Injecting shiny-tracer.js
#> {chromote} JS info 14:27:02.61 shinytest2; jQuery not found
#> {chromote} JS info 14:27:02.63 shinytest2; Loaded
#> {shinytest2} R info 14:27:02.64 Waiting for Shiny to become ready
#> {chromote} JS info 14:27:02.72 shinytest2; jQuery found
#> {chromote} JS info 14:27:02.73 shinytest2; Waiting for shiny session to connect
#> {chromote} JS info 14:27:03.12 shinytest2; Connected
#> {shinytest2} R info 14:27:03.17 Waiting for Shiny to become idle for 200ms within 10000ms
#> {chromote} JS info 14:27:03.18 shinytest2; Waiting for Shiny to be stable
#> {chromote} JS info 14:27:03.27 shinytest2; shiny:busy
#> {chromote} JS info 14:27:06.28 shinytest2; shiny:idle
#> {chromote} JS info 14:27:06.30 shinytest2; shiny:value brussels
#> {chromote} JS info 14:27:06.48 shinytest2; Shiny has been idle for 200ms
#> {shinytest2} R info 14:27:06.48 Shiny app started
#> {shinytest2} R info 14:30:17.79 Setting inputs: 'mu'', ''X'', ''Y'
#> {chromote} JS info 14:30:17.81 shinytest2; inputQueue: adding mu
#> {chromote} JS info 14:30:17.81 shinytest2; inputQueue: adding X
#> {chromote} JS info 14:30:17.81 shinytest2; inputQueue: adding Y
#> {chromote} JS info 14:30:17.82 shinytest2; inputQueue: flushing mu
#> {chromote} JS info 14:30:17.83 shinytest2; inputQueue: flushing X
#> {chromote} JS info 14:30:17.83 shinytest2; inputQueue: flushing Y
#> {chromote} JS info 14:30:17.87 shinytest2; shiny:busy
#> {chromote} JS info 14:30:20.42 shinytest2; shiny:idle
#> {chromote} JS info 14:30:20.46 shinytest2; shiny:value brussels
#> {shinytest2} R info 14:30:20.47 Finished setting inputs. Timedout: FALSE
Once satisfied, we may close the headless connection to stop the recorder:
If you remember, the final step consists of replaying the main
session in parallel. We start shinycannon
with 5 workers
and wait:
target_url <- "http://127.0.0.1:3515"
workers <- 5
system(
sprintf(
"shinycannon recording.log %s --workers %s --loaded-duration-minutes 2 --output-dir run1",
target_url, workers
)
)
# shinycannon replay
#2022-05-09 14:37:18.549 INFO [thread00] - Detected target application type: R/Shiny
#2022-05-09 14:37:18.560 INFO [thread00] - Waiting for warmup to complete
#2022-05-09 14:37:18.554 INFO [thread01] - Warming up
#2022-05-09 14:37:18.562 INFO [progress] - Running: 0, Failed: 0, Done: 0
#2022-05-09 14:37:23.563 INFO [progress] - Running: 1, Failed: 0, Done: 0
Some error message in the shinycannon
logs can be
explained by failures during the {shinytest2}
driver
initialization. If this error persist, best practice is to restart R,
cleanup everything and start again.
The report generation is quite straightforward:
# Close the running app
target$kill()
# Treat data and generate report
df <- shinyloadtest::load_runs("run1")
shinyloadtest::shinyloadtest_report(
df,
"public/index.html",
self_contained = TRUE,
open_browser = FALSE
)
We don’t forget to clean the target app so as to kill the underlying
process. Note that if you want to deploy the report on GitHub Pages, you
have to name it index.html
.
Now, it is time to integrate the current pipeline in a CI/CD workflow. For convenience, we wrap all the previous steps in a single function:
## File: R/audit-app.R
record_loadtest <- function(path, timeout = 15, workers = 5) {
message("\n---- BEGIN LOAD-TEST ---- \n")
# start app + recorder
target <- start_r_bg(shiny_bg, path = path)
recorder <- start_r_bg(recorder_bg)
# start headless chrome (points to recorder!).
# AppDriver also support remote urls.
app <- shinytest2::AppDriver$new(
"http://127.0.0.1:8600",
load_timeout = timeout * 1000
)
app$set_inputs(mu = 4, timeout_ = timeout * 1000)
# clean
app$stop()
# needed to avoid
# java.lang.IllegalStateException: last event in log not a
# WS_CLOSE (did you close the tab after recording?)
Sys.sleep(2)
# shinycannon (maybe expose other params later ...)
target_url <- "http://127.0.0.1:3515"
system(
sprintf(
"shinycannon recording.log %s --workers %s --loaded-duration-minutes 2 --output-dir run1",
target_url, workers
)
)
target$kill()
# Treat data and generate report
df <- shinyloadtest::load_runs("run1")
shinyloadtest::shinyloadtest_report(
df,
"public/index.html",
self_contained = TRUE,
open_browser = FALSE
)
}
Below is the necessary GitHub Actions yaml file. Overall, this will:
on:
push:
branches: [main, master]
pull_request:
branches: [main, master]
name: shiny-loadtest-ci
jobs:
shiny-loadtest-ci:
runs-on: ${{ matrix.config.os }}
permissions:
contents: write
name: ${{ matrix.config.os }} (${{ matrix.config.r }})
strategy:
fail-fast: false
matrix:
config:
- {os: ubuntu-latest, r: 'devel', http-user-agent: 'release'}
- {os: ubuntu-latest, r: 'release'}
- {os: ubuntu-latest, r: 'oldrel-1'}
env:
GITHUB_PAT: ${{ secrets.GITHUB_TOKEN }}
R_KEEP_PKG_SOURCE: yes
steps:
- uses: actions/checkout@v2
- uses: r-lib/actions/setup-r@v2
- uses: r-lib/actions/setup-r-dependencies@v2
with:
cache-version: 2
extra-packages: |
any::shinyloadtest
any::lubridate
any::DT
any::callr
any::shinytest2
any::deSolve
any::attempt
- name: Install shinycannon 💥
run: |
sudo bash -c 'apt-get update; apt-get install -y default-jre-headless; apt-get clean; rm -rf /var/lib/apt/lists/*'
wget https://github.com/rstudio/shinycannon/releases/download/v1.1.3/shinycannon_1.1.3-dd43f6b_amd64.deb
sudo dpkg -i ./*.deb
- name: Run load test 🏥
shell: Rscript {0}
run: |
source("R/audit-app.R")
record_loadtest(path = "app.R");
- name: Deploy to GitHub pages 🚀
if: github.event_name != 'pull_request'
uses: JamesIves/github-pages-deploy-action@4.1.4
with:
clean: false
branch: gh-pages
folder: public
If you want to test it on your end, below are lines of code to setup a RStudio project and link it to GitHub:
# Inside the project
# Use audit GitHub Actions workflow
usethis::use_github_action(url = "https://raw.githubusercontent.com/rstudio/shinytest2/main/inst/gha/app-audit.yaml")
# Copy audit script
dir.create("R", showWarnings = FALSE)
file.copy(system.file("gha/audit-app.R", package = "shinytest2"), "R/audit-app.R")
# Create your app.R file
file.create("app.R")
message("TODO: User - Copy in your app code to `app.R`!")
# To test it locally
source("R/audit-app.R")
record_loadtest("app.R")
# Test the audit with GitHub Actions
usethis::use_description()
usethis::use_git()
usethis::use_github()
usethis::use_github_pages()
If you test it locally within a package, you may want to ignore
public
, recording.log
by adding them in the
.Rbuildignore
file, which will avoid unnecessary warnings
during any future devtools::check()
:
An example is available here.
As shown in the above report, especially in the session duration tab, the app is clearly not able to handle 5 simultaneous user due to the very large computations being performed by the Shiny server:
Even though out of this vignette scope, one quick and significant
optimization would be to set a caching system with
shiny::bind_cache()
. As shown in the following figure,
adding cache is so fast that shinycannon
was able to start
more than 1000 sessions in 2 minutes.
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.